Program Overview: Engineering & Systems Design (ESD) Systems Science (SYS)

Transcription

1 Program Overview: Engineering & Systems Design (ESD) Systems Science (SYS) Chris Paredis Program Director NSF ENG/CMMI Engineering & Systems Design, Systems Science (703) Version 1.13 Dec 1,

2 Disclaimer Any opinions, findings, and conclusions or recommendations expressed in these slides are those of the author/presenter and do not necessarily reflect the views of the National Science Foundation. In October 2015, this presentation was recorded. The video is available at 2

3 Outline Where do the programs fit in the context of NSF? A Story of Design My conceptual framework for systems engineering and design Why a shift towards systems? The difference between Systems Engineering and Engineering Design Systems Science Program details, research examples, and future directions Engineering and Systems Design Program details, research examples, and future directions Discussion 3

4 Program Cluster Division Directorate Where Do ESD and SYS Fit In? Emerging Frontiers in Research and Innovation (EFRI) Engineering Directorate Office of the Assistant Director Deputy Assistant Director Senior Advisor Nanotechnology Engineering Education and Centers (EEC) Civil, Mechanical, and Manufacturing Innovation (CMMI) Chemical, Bioengineering, Environmental, and Transport Systems (CBET) Electrical, Communications and Cyber Systems (ECCS) Industrial Innovation and Partnerships (IIP) Systems Engineering and Design (SED) Advanced Manufacturing (AM) Mechanics and Engineering Materials (MEM) Resilient and Sustainable Infrastructures (RSI) Engineering and Systems Design (ESD) Systems Science (SYS) Sensors, Dynamics, and Control (SDC) Service Enterprise Systems (SES) Operations Research (OR) 4

5 A Story of Design Maybe a Step Towards a Common Understanding Why do designers design artifacts? because it adds value to the designer 1. Individual designer artifact for personal use Designer obtains added value directly from artifact use 2. Individual designer artifact for sale Trading consumer surplus + producer surplus Through trading, both consumer and producer benefit 3. Designer in firm artifact for sale Producer surplus received by firm firm pays designer s salary Organizing in firms is beneficial because it reduces transaction costs 5

6 What do we Mean by Value? Value is an Expression of the Preferences of the Designer Value is an expression of preference the more an outcome is preferred, the higher the value assigned to it A philanthropist may assign high value to an alternative that significantly increases well-being even if it cannot be produced at a profit An environmentalist may assign high value to environmentally friendly, sustainable alternatives A publicly traded company may assign high value to profitable alternatives Value is often expressed in monetary terms If a designer prefers outcome A over outcome B then he/she is willing to exchange A for B plus a dollar amount of Δv = v A v B 6

7 Designing To Improve the Lives of Others But Benefiting the Designer in the Process 1. Understand the customers How could their lives be improved? 2. Identify value opportunities Where can the firm add value by creating something new? 3. Design a new artifact A valuable artifact that can be produced for less than what the customer is willing to pay 4. Sell the artifact to the customer The firm and the customer are better off by receiving a portion of the added value 5. Get paid by the firm A long-term relationship between the designer and the firm is more valuable than carrying the market transaction costs each time 7

8 Designing To Improve the Lives of Others But Benefiting the Designer in the Process 1. Understand the customers How could their lives be improved? 2. Identify value opportunities Where can the firm add value by creating something new? 3. Design Designing, a new artifact Trading, A valuable Organizing artifact in Firms that can be produced Add for Value less than to the what designer the customer and is to willing others. to pay 4. Sell the artifact to the customer The firm and the customer are better off by receiving a portion of the added value 5. Get paid by the firm A long-term relationship between the designer and the firm is more valuable than carrying the market transaction costs each time 8

9 SE & Design: Maximizing Value {Maximize Value} Value Opportunity New Artifact 9

10 Global SE & Design: Maximizing Value Value Opportunities in a Global Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact 10

11 Global SE & Design: Maximizing Value Value Opportunities in a Global Expensive, Scarce Fuel Global Climate Change Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Better Batteries, Better Motors Fuel Efficient, Electric Vehicles 11

12 SE & Design: Maximizing Value Value Opportunities are Restricted by SE&D Capabilities Global Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact 12

13 SE & Design: Maximizing Value Value Opportunities are Restricted by SE&D Capabilities Global Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Apply SE&D Practitioner 13

14 Global SE & Design: Maximizing Value Value Maximization Drives Advances in SE&D Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D Future State of SE&D Standards Tools Methods Theory 14

15 SE & Design: A Search Strategy Value of the Artifact. Maximizing the value π A of an artifact a: A: max a A π A(a) A: max a A E[u π A a ] Overlooks importance of uncertainty Overlooks importance of the search process 15

16 SE & Design: A Search Strategy Value of the Artifact minus Development Cost Maximizing the value π A of an artifact a: A: max a A π A(a) A: max a A E[u π A a ] Overlooks importance of uncertainty Overlooks importance of the search process The search process requires time and resources: A: max a A E u π A a, t A C A 16

17 SE & Design: A Search Strategy Value of the Artifact minus Development Cost Maximizing the value π A of an artifact a: A: max a A π A(a) A: max a A E[u π A a ] The search process requires time and resources: Self Reference! A: max a A E u π A a, t A C A Leads to infinite planning regress heuristics are required 17

18 SE & Design: A Search Strategy Artifact is the Outcome of a Process Maximizing the value π A of an artifact that results from a process p: P: max p P E u π A a p, t p p C p (p) No longer self-referential, but still dynamic in the sense that future process steps depend on the outcomes of previous process steps Search strategy, p, and resulting artifact are inextricably linked Must make a tradeoff between artifact value and search time & cost 18

19 SE & Design: A Search Strategy Search Process is Performed by an Organization Maximizing the value π A of an artifact that results from a process p, performed by and organization o: O: max o O p P E u π A a p, o, t p p, o C o p, o i(o) Socio-technical problem Should build on organizational sociology, game theory, mechanism design, A crucial part of systems engineering and design is the choice of search strategy and organizational structure 19

20 Outline Where do the programs fit in the context of NSF? A Story of Design A conceptual framework for systems engineering and design Why a shift towards systems? The difference between Systems Engineering and Engineering Design Systems Science Program details, research examples, and future directions Engineering and Systems Design Program details, research examples, and future directions Discussion 20

21 Where do SYS and ESD fit in? Why a Shift Towards Systems? Engineering Design & Innovation (EDI) ESD & SYS The EDI program supports research leading to design theory and to tools and methods that enable implementation of the principles of design theory in the practice of design across the full spectrum of engineered products. Complex Engineered Systems Multiple disciplines Multiple stakeholders Multiple concerns Complex interactions Uncertain outcomes Explicit focus on a Holistic, Systems Perspective We can no longer limit ourselves to just a mechanical engineering perspective Unless we adapt, we become irrelevant 21

22 Engineering Design Systems Engineering Relative Importance of Artifact vs. Process & Organization Engineering Design Artifact-focused Later in development process Applies to relatively simple systems or components Systems Engineering Process and organization-focused Early in development process Applies to more complex systems Distinction is somewhat artificial communities would benefit from more interaction 22

23 Global SE & Design: Maximizing Value Value Maximization Drives Advances in SE&D 2 Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D 4 Future State of SE&D Standards Tools Methods Theory

24 Global Where do SYS and ESD fit in? Value Maximization Drives Advances in SE&D ESD Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D ESD Future State of SE&D Standards Tools Methods Theory SYS ESD 24

25 Outline Where do the programs fit in the context of NSF? A Story of Design A conceptual framework for systems engineering and design Why a shift towards systems? The difference between Systems Engineering and Engineering Design Systems Science Program details, research examples, and future directions Engineering and Systems Design Program details, research examples, and future directions Discussion 25

26 Systems Science (SYS) Theoretical Foundation for SE & Design SE&D Practice Concept Definition Requirements Engineering System Architecting Interface Definition Functional Analysis Tradespace Analysis Risk Management Gap SE&D Require an Integrative Scientific Approach Foundations Systems Theory Decision Theory Probability Theory Economics Organizational Theory Psychology Behavioral Economics 26

27 Systems Science (SYS) Theoretical Foundation for SE & Design SE&D Practice Concept Definition Requirements Engineering System Architecting Interface Definition Functional Analysis Tradespace Analysis Risk Management Theoretical Foundation for Systems Engineering & Design Foundations Systems Theory Decision Theory Probability Theory Economics Organizational Theory Psychology Behavioral Economics 27

28 Systems Science (SYS) Theoretical Foundation for SE & Design SE&D Practice Concept Definition Requirements Engineering System Architecting Interface Definition Functional Analysis Tradespace Analysis Risk Management Theoretical Challenge: Foundation for Rigorous Systems & Engineering Pragmatic Foundations Systems Theory Decision Theory Probability Theory Economics Organizational Theory Psychology Behavioral Economics 28

29 Systems Science (SYS) Theoretical Foundation for SE & Design SE&D Practice Concept Definition Requirements Engineering System Architecting Interface Definition Functional Analysis Tradespace Analysis Risk Management Theoretical Explanatory Models Improved Methods & Tools Empirical Charact. / Falsification Foundations Systems Theory Decision Theory Probability Theory Economics Organizational Theory Psychology Behavioral Economics 29

30 Systems Science (SYS) Program Overview Role of Program Leadership in grounding systems engineering and design practice on a rigorous theoretical foundation Focus Theoretical foundation of systems engineering & design Application domain independent Special emphasis on Complex Engineered Systems Draw on or extend established theory in mathematics, economics, organizational theory, social psychology, and other relevant fields Empirical research is in scope when characterizing a theoretical model An integrative scientific approach to support the development of complex engineered systems 30

31 Systems Science (SYS) Some Research Examples Knowledge Representation How can design knowledge best be captured and represented formally? Ideation and Cognition How should tacit knowledge be elicited, expressed and incorporated in engineering ideation and decision making? Which social and psychological processes are most important to successfully identify the outcomes of a particular design alternative, from a holistic, systemsthinking perspective? Uncertainty and Prediction How should one quantify and manage uncertainty from initial engineering design predictions through to operation and maintenance of large scale systems? Engineering Decision Making How should decisions be framed and sequenced to search a design space efficiently and effectively? Engineering Organizations What is the relation of the structure of an engineering organization to design outcomes? 31

32 Systems Science (SYS) Future Directions Processes: Search Strategy, Guidance and Control Design as a search process What are good search strategies? Appropriate abstractions? Metrics for process control? Influence of uncertainty? Organizations: Decomposition, Communication and Incentivisation How to decompose problems and delegate the decomposed parts? Impact of incentive structures? How to facilitate communication between experts with disparate backgrounds towards ideation and analysis in design? Modeling: Creation, Use and Assessment of Models Which modeling formalisms are most appropriate when? What are the cognitive models of modeling? How best to teach modeling? How to facilitate reuse and sharing? How to assess and characterize the accuracy and applicability of models? Research Methodology We want to improve design, but we don t agree on what good means or how to assess goodness Given that the theoretical foundations need to be operationalized into pragmatic, domain-specific methods and tools that are based on approximations of the foundations, how can we efficiently and effectively derive such methods and tools, and characterize their performance and applicability? 32

33 Global Where do SYS and ESD fit in? Value Maximization Drives Advances in SE&D ESD Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D ESD Future State of SE&D Standards Tools Methods Theory SYS ESD 33

34 Global Where do SYS and ESD fit in? Value Maximization Drives Advances in SE&D ESD Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D ESD Future State of SE&D Standards Tools Methods Theory SYS ESD 34

35 Engineering & Systems Design (ESD) Building on the Theoretical Foundation SE&D Practice Concept Definition Requirements Engineering System Architecting Interface Definition Functional Analysis Tradespace Analysis Risk Management Challenge: Theoretical Rigorous & Foundation Pragmatic for -Specific Systems Engineering Approximations Foundations Systems Theory Decision Theory Probability Theory Economics Organizational Sociology Psychology Behavioral Economics 35

36 Engineering & Systems Design (ESD) SE&D Methods & Tools for a Specific As the context changes, SE&D must adapt by operationalizing the theoretical foundation for each specific context Increasing complexity Shorter lifecycle times Decentralization Systems of Systems Mass-customization Human-centered Cloud-based highperformance computing Big data Immersive data visualization Net-enabled collaboration 36

37 Engineering & Systems Design (ESD) SE&D Methods & Tools for a Specific As the context changes, SE&D must adapt by operationalizing the theoretical foundation for each specific context A new context implies new approximations: Synthesis heuristics which architecture patterns? Analysis idealizations which formalisms, fidelity? SE&D process heuristics Big when data to do what? Organizational structure who does what? Increasing complexity Shorter lifecycle times Decentralization Systems of Systems Mass-customization Human-centered Cloud-based highperformance computing Immersive data visualization Net-enabled collaboration 37

38 Tool Implementation Approximations Foundations Engineering & Systems Design (ESD) An Illustrative Example Information and Communications Technology Decision Support Tool for Design for X Organizational Structure Domain Knowledge for X Decision Model for X Architecture heuristics Analysis-model idealizations Uncertainty characterizations Knowledge Representation Sociology Economics Probability Theory Decision Theory Psychology 38

39 Engineering & Systems Design (ESD) Program Overview Role of Program Leadership in advancing engineering and systems design practices for current and future global contexts, by combining rigor and pragmatism Program Focus Operationalizing the theoretical foundation in specific contexts» Develop pragmatic methods to apply the theory efficiently and effectively in a specific economic, socio-political, environmental and technological context Rigorously characterizing current and novel methods» In which context and under which assumptions is a method effective?» Rigorously gather theoretical and empirical evidence, regarding current and improved practices Education» Develop effective teaching strategies rigorously based on cognitive models 39

40 Engineering & Systems Design (ESD) Future Research Directions Design for X X = Specific Application Domain energy systems, consumer products, additive mfg, X = Specific Concern resilience, sustainability, usability, manufacturability, Novel Information and Communication Technologies in SE&D immersive visualization and human-computer interaction, social networking and netenabled collaboration, modeling frameworks and languages, data mining and analytics, high-performance computing and cloud-computing Novel Modeling Formalisms & Algorithms Formalisms and algorithms for representing and manipulating form, function and behavior; algorithms for analysis, simulation, optimization, or reasoning; algorithms for prediction, uncertainty quantification and propagation Novel Integrated Frameworks for SE&D Frameworks combining concept generation, gradual specification refinement, models at different abstractions, uncertainty characterization, optimization, human input, HPC, visualization, to achieve efficient and effective search. We Need to Rigorously Characterize and Assess Domain-Specific Methods 40

41 Program Opportunities & Logistics What you need to know to submit your proposal? Unsolicited proposals submission windows Fall: September 1-15 Spring: February 1-15 Typical scope of proposals: 1-2 PIs, 1-2 PhD students, 3 yrs CAREER proposals accepted for both SYS and ESD Deadline: sometime mid-july 2015 Solicitation number: NSF to be updated for 2015 Budget: $500,000 Interested in being a panelist? me a 1-page description of your background & interests More info at: ESD: SYS: 41

42 Related Programs How can you expand your funding base? GOALI: Grant Opportunities for Academic Liaison with Industry DEMS: Design of Engineering Material Systems RSB: Decision Frameworks for Multi-Hazard Resilient and Sustainable Buildings CPS: Cyber-Physical Systems ACI: Advanced Cyberinfrastructure CDS&E: Computational and Data-Enabled Science and Engineering INSPIRE: see NSF We will specifically consider proposals that tie SE&D to organizational sociology or cognitive science other interdisciplinary topics will be considered also. Additional opportunities will follow Subscribe to NSF News 42

43 Summary Advancing the State of Knowledge in Systems Engineering and Design Global ESD Economic Environmental {Maximize Value} Socio-Political Technological Value Opportunity New Artifact Current State of SE&D Standards Tools Methods Theory Theoretical Foundation Advance SE&D Enabling Technology Researcher Practitioner Apply SE&D ESD Future State of SE&D Standards Tools Methods Theory SYS ESD 43

44 Some References & Introductory Material H.A. Simon, Sciences of the Artificial 3 rd Edition, MIT Press, G. Hazelrigg, Fundamentals of Decision Making for Engineering Design and Systems Engineering, G.S. Parnell, P.J. Driscoll, D.L. Henderson, Decision Making in Systems Engineering and Management (2 nd Edition), Wiley, J.M. Bernardo, A.F.M. Smith, Bayesian theory, Wiley, R. Gibbons, Game Theory for Applied Economists, Princeton University Press, D. Kahneman, Thinking, Fast and Slow, Farrar, Straus and Giroux, J. Brickley, J. Zimmerman Jr., C.W. Smith, Managerial Economics & Organizational Architecture (5 th Edition), McGraw-Hill, B.D. Lee, C.J.J. Paredis, A Conceptual Framework for Value-Driven Design and Systems Engineering, 24 th CIRP Design Conference, Milan, Italy, April 14-16,